Target SVP says its real AI moat isn't the models — it's everything built around them
Target's competitive advantage comes from the infrastructure and systems built around AI models rather than the models themselves. Agents at Target earn autonomy gradually and are deployed only for problems that create significant value, integrated across supply chain, replenishment, and demand forecasting systems.
Read full story →Meta Bets Its Next Revenue Line on Personal AI Agents
Meta announced personal AI agents as a core component of its future revenue strategy during second-quarter earnings on July 29, 2026, with CEO Mark Zuckerberg calling them "the foundation for our next wave of products and revenue lines." The company has not yet launched this consumer agent business but plans to provide additional details in coming months.
At Waymo, an AI project isn't ready until its evals are — not when the model performs well
Waymo uses "eval-centric development," making continuous evaluation a core engineering practice rather than a final deployment check. The company has driven over 220 million fully autonomous miles with 17 times fewer serious crash injuries than human drivers.
Enterprise AI agents can't talk to each other, can't be trusted with permissions, and can't be audited — 5 startups are already fixing that
Enterprise AI agents lack infrastructure to communicate, be authorized, and be audited effectively. Five startups are developing solutions including BAND, which creates a coordination layer allowing agents to discover each other, delegate tasks conversationally, and return summarized results to users.